Crowdsourcing challenges are fast emerging as an effective tool for solving complex innovation problems. The main strength of the crowdsourcing model is that it brings together a large number of diverse people from all over the world to focus on solving a problem. This openness, however, results in a large number of solutions that are not appropriate, and this inhibits organizations from leveraging the value of crowdsourcing efficiently and effectively. It is therefore essential to identify ways to increase the appropriateness of solutions generated in a crowdsourcing challenge. This paper takes a step towards that by exploring what motivates the crowd to participate in these challenges and how these motivations relate to solution appropriateness. Drawing on data from InnoCentive, one of the largest crowdsourcing platforms for innovation problems, this paper shows that the various types of motivation driving crowd members to participate were related in different ways to the appropriateness of the solutions generated. In particular, intrinsic and extrinsic motivation were positively related to appropriateness whereas for learning and prosocial motivation the relationship was negative. The association between social motivation and appropriateness was not significant. The results have important implications for how to better design crowdsourcing challenges.

Introduction

Advances in digital technologies are fundamentally transforming the innovation practices of organizations. These technologies have blurred the boundaries of innovation processes and in turn have provided organizations with unprecedented opportunities in their search for innovation (Afuah and Tucci, 2012; Harhoff and Lakhani, 2016; Nambisan et al., 2017). Interested in leveraging the potential of digitization, organizations are increasingly using crowdsourcing challenges (i.e., open competitions in which crowd members compete to generate the best solution(s) in return for a financial prize) to tackle complex innovation problems. From breakthroughs in the discovery of new drugs to designing algorithms that can transform diagnosis of various diseases, these challenges have proved to be an effective way of harnessing the creative potential of the crowd to solve thorny problems (Acar and van den Ende, 2015; Lakhani et al., 2013; Saez-Rodriguez et al., 2016). The main value of the crowdsourcing model for innovation is that a large and diverse group of people are attracted to engage in problem-solving – not only experts from within the problem domain but also outsiders such as scientists from other domains or hobbyists who may have fresh ideas and perspectives to contribute (Acar and van den Ende, 2016; Boudreau et al., 2011; Jeppesen and Lakhani, 2010). This scale and diversity, however, may inhibit organizations from harnessing the creative potential of the crowd effectively or may discourage them from using crowdsourcing altogether. The sheer volume of solutions generated in crowdsourcing can be overwhelming for many organizations (Blohm et al., 2013).